Planet Georezo » December 30, 2011

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30 décembre 2011
22:42
Mapping Air PollutionGIS Lounge
sur Planet Geospatial - http://planetgs.com

Pulling real time data from the city government of Madrid, Into the Air is a project led by Nerea Calvillo (along with a team of architectural students, anthropologists, and designers) to map out air pollutants over the Spanish city. The project was originally developed at Visualizar’08, an annual workshop/seminar that focused that year’s efforts on urban data visualization. The [...]

22:26
Matt Sheehan: Mobile GIS Feature Editing
sur Planet OSGeo

This is part 2 of a discussion on mobile GIS and feature editing. In part 1 we began the discussion. Here we spoke about saving basemap tiles and shapefiles to the mobile device. How shapefiles can be represented (overlaid) on the map in a number of, less than perfect, ways. We discussed other [read full article]

22:01
Happy New Year!!!LiDAR News
sur Planet Geospatial - http://planetgs.com

Thanks for all the support this year. My prediction is that 2012 is going to surprise to the upside. With everyone pulling together (being a rower) we can make that happen. Continue reading →

Click Title to Continue Reading...

21:53
Joachim Van der Auwera: Geomajas GIS framework 2011 roundup
sur Planet OSGeo

2011 was a very productive year for the Geomajas project. There was a lot of progress in many areas. Before listing everything that happened in the last year, let’s start on what did not happen. There was no new release in the last six months. That is not good. There have been some great developments, [...]
19:43
Gary Sherman: QGIS Plugin of the Week: Points to Paths
sur Planet OSGeo
This week we highlight the Points to Paths plugin, a handy way to convert a series of points into line features. This plugin lets you “connect the dots” based on an common attribute and a sequence field. The attribute field determines which points should be grouped together into a line. The sequence field determines the order in which the points will connected. The output from this plugin is a shapefile.

Let’s take a look at some example data. Here we have some fictional wildlife tracking data for two moose. The tracking data is in shapefile format, but you can use any vector format supported by QGIS. The tracking data is symbolized by our two animals: Moose1 and Moose2:

The moose_tracks layer has an animal tracking id field (animal_tid) and a sequence field (id). This is all we need to convert the individual observations into a line feature that represents the animals path.
Installing the Plugin
The Points to Paths plugin is installed like all other Python plugins. From the the Plugins menu in QGIS, choose Fetch Python Plugins. This brings up the plugin installer. To find the plugin, enter points to in the Filter box, then select Points to Paths from the list. Once it’s highlighted, click the Install plugin button. This will download the plugin from the repository, install it, and load it into QGIS.
Using the Plugin
Let’s convert the tracking data to paths. To get started, choose Plugins->Points to Paths from the menu or click on the Points to Paths tool on the Plugin toolbar. This brings up the PointsToPaths dialog box where we specify the paramaters needed to create the paths. Below is the completed dialog for our moose tracks:

The first drop-down box contains a list of the vector layers loaded in QGIS—in our case we have just one: moose_tracks. For the group field drop-down we chose the field that contains the tracking identifier for each animal. This determines which points will be selected and grouped to form an individual line. The point order field drop-down specifies the field that contains the ordering for the observations. In this case, the id field is incremented with each observation and can be used to construct the paths. We don’t have a date/time field in this data, but your observations may be sequenced in this way. The Python date format field allows you to specify a format string so the plugin can determine how to sequence your points based on date/time.

The last thing we need to specify is the output shapefile. You can do this by typing in the full path to a new shapefile or by using the Browse button.

With these options set, clicking the OK button will create the new shapefile containing the paths created from our point observations. Once the shapefile is created, the plugin gives you the option to add the new shapefile directly to QGIS.
The Result
The result of our simple example are shown below:

We symbolized the individual tracks using the Categorized renderer on the Style tab of the vector properties dialog. You can see we now have a track for each animal. The attribute table created by the plugin contains the following fields:
- group – the name of the animal taken from the field we chose as the group field
- begin – the value of the first point order field used to create the path
- end – the value of the last point order field used to create the path
In our data, group contains the animal name, begin the value of the lowest id field for animal, and end contains the greatest id value. In a more typical data set, begin and end would contain the start and end date/time values for the observation. Labeling the observation points with our sequence field or date/time values would allow us to determine the direction of movement.

If you have point data that represent a movement of an object, this plugin is a great way to convert it into a path that can be used for visualization, analysis, or map composition.

19:43
QGIS Plugin of the Week: Points to PathsSpatial Galaxy
sur Planet Geospatial - http://planetgs.com
This week we highlight the Points to Paths plugin, a handy way to convert a series of points into line features. This plugin lets you “connect the dots” based on an common attribute and a sequence field. The attribute field determines which points should be grouped together into a line. The sequence field determines the order in which the points will connected. The output from this plugin is a shapefile.

Let’s take a look at some example data. Here we have some fictional wildlife tracking data for two moose. The tracking data is in shapefile format, but you can use any vector format supported by QGIS. The tracking data is symbolized by our two animals: Moose1 and Moose2:

The moose_tracks layer has an animal tracking id field (animal_tid) and a sequence field (id). This is all we need to convert the individual observations into a line feature that represents the animals path.
Installing the Plugin
The Points to Paths plugin is installed like all other Python plugins. From the the Plugins menu in QGIS, choose Fetch Python Plugins. This brings up the plugin installer. To find the plugin, enter points to in the Filter box, then select Points to Paths from the list. Once it’s highlighted, click the Install plugin button. This will download the plugin from the repository, install it, and load it into QGIS.
Using the Plugin
Let’s convert the tracking data to paths. To get started, choose Plugins->Points to Paths from the menu or click on the Points to Paths tool on the Plugin toolbar. This brings up the PointsToPaths dialog box where we specify the paramaters needed to create the paths. Below is the completed dialog for our moose tracks:

The first drop-down box contains a list of the vector layers loaded in QGIS—in our case we have just one: moose_tracks. For the group field drop-down we chose the field that contains the tracking identifier for each animal. This determines which points will be selected and grouped to form an individual line. The point order field drop-down specifies the field that contains the ordering for the observations. In this case, the id field is incremented with each observation and can be used to construct the paths. We don’t have a date/time field in this data, but your observations may be sequenced in this way. The Python date format field allows you to specify a format string so the plugin can determine how to sequence your points based on date/time.

The last thing we need to specify is the output shapefile. You can do this by typing in the full path to a new shapefile or by using the Browse button.

With these options set, clicking the OK button will create the new shapefile containing the paths created from our point observations. Once the shapefile is created, the plugin gives you the option to add the new shapefile directly to QGIS.
The Result
The result of our simple example are shown below:

We symbolized the individual tracks using the Categorized renderer on the Style tab of the vector properties dialog. You can see we now have a track for each animal. The attribute table created by the plugin contains the following fields:
- group – the name of the animal taken from the field we chose as the group field
- begin – the value of the first point order field used to create the path
- end – the value of the last point order field used to create the path
In our data, group contains the animal name, begin the value of the lowest id field for animal, and end contains the greatest id value. In a more typical data set, begin and end would contain the start and end date/time values for the observation. Labeling the observation points with our sequence field or date/time values would allow us to determine the direction of movement.

If you have point data that represent a movement of an object, this plugin is a great way to convert it into a path that can be used for visualization, analysis, or map composition.
19:29
Homeschool Cartography CoursesGIS Lounge
sur Planet Geospatial - http://planetgs.com

If you live near Portland, Maine and have homeschooled children, there is a cartography course being offered through the Osher Map Library and Smith Center for Cartographic Education of the University of Southern Maine. The four-part homeschooling cartography course is offered at two levels: intermediate for children aged 10-12 and secondary students aged 13-16. The classes [...]

19:25
Revue de presse de la semaine du 26 Décembre
sur Geotribu

52 semaines - 52 revues de presse !!! Nous avons réussi à tenir nos engagements. Ce n'est pas une sinécure - le temps nous manquant parfois. Mais le plaisir de vous voir nombreux à nous lire nous incite à continuer à écrire, à vous faire partager nos découvertes et parfois à faire du lobbying pour des causes - géographiques - qui nous semblent pertinentes.

en lire plus

17:05
Sean Gillies: Shapely from the outside
sur Planet OSGeo

Right before the the start of my holiday, I stumbled onto a post from a GIS blog I'd never seen before. It's an older post that compares Shapely to OGR's Python module and GeoScript. As comments are disabled on that post, I'll make a few here. At the time the post was written, Shapely 1.2.8 was released and the manual was fully mature. Greg Corradini writes:

Shapely is a little bit different than OGR and GeoScript. One big difference is that you can’t read and write to file formats with it. The idea, at least the idea that I’ve taken from it’s website, is that Shapely is a “swiss-army-knife” spatial analysis tool — it does some things really really fast and pythonic but it isn’t going to fix a flat tire. Or something like that.

Shapely is more limited than a Swiss Army knife. It's just a wrapper for the GEOS library, using idiommatic Python. It tries to do one thing – or rather, one fairly large set of related things – very well. It doesn't read or write GIS data formats, so if it's a Swiss Army knife it's one without can and bottle openers.

The coolo-neato things about Shapely include the ability to serialize/deserialize to/from data formats that implement a GeoJson-like interface and to/from numpy arrays. There’s also a couple helpful methods — linemerge and polygonize — that it wraps from the GEOS library.

I'm glad to see that somebody appreciates the GeoJSON-like Python geo interface.

These methods aren’t as easy to reach in GeoScript or OGR built with GEOS support off the proverbial ‘shelf’ because you’d have to call Java libraries in the case of GeoScript and C++ libraries using Python ctypes. Shapely makes using these methods easy, even though you could develop your own wrappers to get at them in GeoScript and OGR with GEOS support.

I hadn't thought of these functions as killer features. I suspect they're probably available in osgeo.ogr by now.

I want to say one last thing about Shapely, though it might reflect some naivete on my part about the functionality of this tool. It seems to me that you can do about 80% of what Shapely does if you build OGR against GEOS and use those bindings. Although it might be more pythonic, optimized in certain ways and syntactically simpler, I’m still unsure who the users are and why. I think the TileStache project uses this library on the backend. I’m interested to find more examples.

I used to work in a GIS shop where at least half of the work was taking some data in one obscure format, doing something relatively simple to it (reprojection, for example), and writing it out in some other arcane format. Shapely by itself is practically useless for that kind of work, and I understand that it's purpose can be baffling to the programming GIS analyst. I think I might have found it baffling before my career change.

Finally, Corradini writes:

Since Shapely can’t read or write geometries we have to lean on an existing interop library. Example 3 will use OGR for reads and writes.

Or better yet: Fiona.

It's an interesting post, and the way it weighs a few different software packages is rare these days. It also has me thinking about whether I should be benchmarking Shapely and Fiona versus GeoScript. Assuming the testit module is supported by Jython and produces directly comparable numbers (because I won't be able to benchmark my C Python modules in the same process), it should be pretty easy to do.

17:05
Shapely from the outsideSean Gillies Blog
sur Planet Geospatial - http://planetgs.com

Right before the the start of my holiday, I stumbled onto a post from a GIS blog I'd never seen before. It's an older post that compares Shapely to OGR's Python module and GeoScript. As comments are disabled on that post, I'll make a few here. At the time the post was written, Shapely 1.2.8 was released and the manual was fully mature. Greg Corradini writes:

Shapely is a little bit different than OGR and GeoScript. One big difference is that you can’t read and write to file formats with it. The idea, at least the idea that I’ve taken from it’s website, is that Shapely is a “swiss-army-knife” spatial analysis tool — it does some things really really fast and pythonic but it isn’t going to fix a flat tire. Or something like that.

Shapely is more limited than a Swiss Army knife. It's just a wrapper for the GEOS library, using idiommatic Python. It tries to do one thing – or rather, one fairly large set of related things – very well. It doesn't read or write GIS data formats, so if it's a Swiss Army knife it's one without can and bottle openers.

The coolo-neato things about Shapely include the ability to serialize/deserialize to/from data formats that implement a GeoJson-like interface and to/from numpy arrays. There’s also a couple helpful methods — linemerge and polygonize — that it wraps from the GEOS library.

I'm glad to see that somebody appreciates the GeoJSON-like Python geo interface.

These methods aren’t as easy to reach in GeoScript or OGR built with GEOS support off the proverbial ‘shelf’ because you’d have to call Java libraries in the case of GeoScript and C++ libraries using Python ctypes. Shapely makes using these methods easy, even though you could develop your own wrappers to get at them in GeoScript and OGR with GEOS support.

I hadn't thought of these functions as killer features. I suspect they're probably available in osgeo.ogr by now.

I want to say one last thing about Shapely, though it might reflect some naivete on my part about the functionality of this tool. It seems to me that you can do about 80% of what Shapely does if you build OGR against GEOS and use those bindings. Although it might be more pythonic, optimized in certain ways and syntactically simpler, I’m still unsure who the users are and why. I think the TileStache project uses this library on the backend. I’m interested to find more examples.

I used to work in a GIS shop where at least half of the work was taking some data in one obscure format, doing something relatively simple to it (reprojection, for example), and writing it out in some other arcane format. Shapely by itself is practically useless for that kind of work, and I understand that it's purpose can be baffling to the programming GIS analyst. I think I might have found it baffling before my career change.

Finally, Corradini writes:

Since Shapely can’t read or write geometries we have to lean on an existing interop library. Example 3 will use OGR for reads and writes.

Or better yet: Fiona.

It's an interesting post, and the way it weighs a few different software packages is rare these days. It also has me thinking about whether I should be benchmarking Shapely and Fiona versus GeoScript. Assuming the testit module is supported by Jython and produces directly comparable numbers (because I won't be able to benchmark my C Python modules in the same process), it should be pretty easy to do.
16:49
New ArcGIS National Geographic Basemap Layer (Demo)AnyGeo - GIS, Maps, Mobile and Social Location Technology
sur Planet Geospatial - http://planetgs.com

Are you an ArcGIS.com user? If so then you’ll now find another new option when selecting your basemap style as Esri has recent;y added the National Geographic basemap option. This via a recent blog post on the ArcGIS Desktop blog… In the Add Basemap dialog, the Shaded Relief basemap entry has been removed in order [...]
16:36
Friday’s Food for Thought: 2012 Predictions and Much Moregot geoint?
sur Planet Geospatial - http://planetgs.com

Welcome to the Friday’s Food for Thought post from got geoint? This is our last FFFT post for 2011. It’s been quite a year for the GEOINT sector, which begs the question: What’s in store for 2012? We try to dive into this and much more in today’s post. And, if you’re a Federal employee there’s still time to donate to USGIF academic programs through the USGIF campaign. Help the future of the GEOINT trade craft, donate now to USGIF CFC #88693. Check out some of the good things the Combined Federal Campaign of the National Capital Area (CFCNCA) is doing to help local charities this holiday season here.

So, since the news-cycle in inundated with stories today about 2012 predictions, we decided to pull together the most interesting and eclectic stories for your reading pleasure. Yes, it certainly covers a wide range of topics, but as GEOINT professionals, aren’t we also very multilayered as people?

10 Education Predictions for 2012

Larry Ferlazzo, an English teacher at Luther Burbank High School in Sacramento, California and popular education blogger, has provided his top 10 education predictions for 2012. Ferlazzo covers a wide range of subject such as the new concept of Social and Emotional Learning (SEL), but what about geography education becoming a major priority? Check out the full list here.

2012 Tech Predictions

What is 2012 likely to bring to the tech industry and its users? IDG — the publisher of InfoWorld, Computerworld, Network World, CIO, CSO, ITworld, PC World, Macworld, and other tech publications throughout the globe — surveyed its editors to gaze into their crystal balls and predict a key trend or development for 2012, as well as select their key story for 2011. The death of Apple CEO Steve Jobs and the rise of social media as a tool of protest topped a diverse roundup of nominees. Click here to check out these predictions.

Boxing Predictions for 2012

For you boxing fans out there, SI.com has pulled together the top boxing predictions for 2012. Some key predictions are that Manny Pacquiao will finally lose in 2012 and it won’t be against Floyd Mayweather; Cruiserweight will be one of boxing’s most promising, under-the-rader weight divisions; and look for the rapid ascent of Gary Russell Jr. to continue as 2012 enters full swing. Be sure to check out more here.

NFL Predictions for 2012

Oh, and for you football fans out there, SI.com also compiled its NFL predictions for 2012, which include the Saints winning their second Super Bowl in three years, beating the Ravens; the Colts and Peyton Manning parting ways; and Packers backup QB Matt Flynn will generate a lot of interest this off season. Check out more here.

5 Medical Advances Predicted for 2012

Great medical feats were accomplished in 2011. Dallas Wiens became the first recipient of a full-face transplant in the United States, Arizona congresswoman Gabrielle Giffords survived a gunshot to her brain, and HIV researchers found a way to lower an infected person’s chance of transmitting the virus to sexual partners by 96 percent. What significant advances can we expect in 2012? Here are five predictions, provided to MyHealthNewsDaily by experts in their fields.

Facebook 2012: What the Future Holds for the Social Media Powerhouse

What do you do after your site grows to 800 million users and expands to 1 trillion pageviews per month? Why, plan a $100 billion IPO, of course! Going public is clearly the biggest thing on tap for Facebook in 2012, but the world’s most populated social network and its users have a lot to look forward to over the coming year. From the maturation of Mark Zuckerberg as a leader to Facebook’s growth as a media platform to a looming collision with the world’s biggest tech companies, 2012 is poised to be one of the most important years in the company’s short history. Check out Mashable.com’s predictions for 2012 for Facebook here.

Strangest One-Hit Wonder Song About the Future

So what does the future truly hold for the human race? One-hit wonders Zager & Evan try to tackle this with its ambitious single “In the Year 2525 (Exordium and Terminus).” This beloved cult classic is an operatic narrative predicting bizarre evolutionary turns with every verse. We hope you enjoy and see you in the year 2012!

16:11
Joyeuse année 2012 !
sur arcOrama, un blog sur les SIG, ceux d ESRI en particulier

Avec plus de 54000 visiteurs uniques cette année, le lectorat d'arcOrama a progressé de 60% en 2011. Je profite donc de cet article pour vous remercier de votre fidélité.

Avec l'arrivée d'ArcGIS 10.1 à la fin du printemps, l'année 2012 sera riche en innovations et en actualités et nous prendrons plaisir à vous décrypter. Les évolutions importantes autour d'ArcGIS Online vont faire de 2012, une année charnière pour le déploiement de votre système ArcGIS sur le Cloud.

Inspiré par les voeux de nos confrères d'Esri Belux, j'ai choisi ce petit clin d'œil sous forme de WebMap ArcGIS Online pour vous souhaiter nos meilleurs voeux pour cette nouvelle année.

Si vous souhaitez retrouver ces différents bâtiments extraits du fond de carte World Imagery d'ArcGIS Online, vous pouvez afficher cette présentation réalisée avec ArcGIS Explorer Online.

15:54
Free and Open Source GIS Ramblings: Conditional Labels in QGIS
sur Planet OSGeo
The latest QGIS development build (1.9.90) has a new feature “expression based labeling” which can be used to create conditional labels. One typical use case would be if you want to label only certain (high-level) road classes in your road layer. By default, QGIS labels the features rather randomly:

default labeling

How can we label only the more important roads? Here is an example using OSM data imported into PostGIS using osm2po:

If you have loaded OSM using osm2po, your OSM table will contain a “clazz” attribute. (Check osm2po.config for the exact mapping.) To label only motorways, trunks, primary and secondary roads and nothing else, I wrote this labeling expression:
```
substr(osm_name, 0, (clazz = 11 or clazz = 13 or clazz = 15 or clazz = 21)*-1)
```
If clazz equals 11, 13, 15 or 21, the expression returns the value of osm_name. Otherwise it returns an empty string. (All checks will return false or 0 which causes the function to evaluate to substr(osm_name,0,0).) Kudos to Giuseppe Sucameli who explained this on the mailing list.

expression based "conditional" labels

15:27
Google Maps can Take You to Warp Drive
sur Google Maps Mania

Google Maps on Warp Drive

Some lucky folks in Turlock, California actually get to live in Warp Drive. Their neighbors, on nearby streets, live on roads called Picard Lane, Ryker Court and Crusher Avenue. I think I spot a theme here.

Google Maps Carpets

David Hanauer is making carpets with designs inspired by Google Maps satellite views.

Not to be outdone Ben Seven came up with this great idea for a map design for a lampshade.

14:48
The Year 2011 in Google EarthGoogle Earth Blog
sur Planet Geospatial - http://planetgs.com

Google Earth had a tremendous year in 2011. Our most popular story of the year, by far, was from people searching for Osama bin Laden's compound in May. There was also quite a bit of interest in resources for the Japanese earthquake, as Google Earth is an excellent platform to share imagery and information for an event like that.

Here's a quick look back at the biggest stories for each month of 2011.

January

There wasn't any major Google Earth news in January, but we saw cool things like Louis Zamperini's journey mapped in Google Earth and Google hosted the 2011 GSA Penrose Conference.

February

Google brought art galleries into Street View and GeoEye provided some amazing imagery of the protests in Egypt.

March

Google was quick to respond to the Japanese earthquake and tsunami with high-resolution post-earthquake imagery shortly after the disaster and 3DConnexion sold their one millionth 3D mouse.

April

This month Google made some great enhancements to the mountain layer in Google Earth and we got some fresh imagery from the tornadoes that ravaged Alabama.

May

Google added 3D building support for Android tablets and people flocked to Google Earth to try to see Osama bin Laden's compound.

June

More 3D trees started appearing in a few cities and fresh imagery was released from the Nabro Volcano in Africa.

July

July brought the 100th anniversary of the discovery of Machu Picchu, South Sudan became a new country and the final space shuttle launch was tracked in Google Earth.

August

In August we showed you some fresh imagery of the damage from Hurricane Irene and we explored the true size of the Stone Mountain carving.

September

Google Earth 6.1 was released, bringing some nice new KML features with it. We also looked at the past, present and future of the World Trade Center complex in New York on the 10-year anniversary of the 9/11 attacks.

October

Peter Olsen created an excellent 3D model of the MLK National Memorial and Google Earth reached the one billion download milestone.

November

We took an early look at the 2012 London Olympic venues and enjoyed the cool new Fluid Nebula tool for Google Earth.

December

We played with Google Earth on the Samsung Galaxy Nexus and saw a new island being formed in the Red Sea by a volcano.

It's been another amazing year for Google Earth. What was your favorite story of the year?

14:33
Sourcepole: Raster resampling in QGIS
sur Planet OSGeo

QGIS already offers a lot of possibilities to visualize raster data (contrast enhancement, color map, handling of transparent pixels, …) Last year, Radim Blazek refactored the raster provider interface and added on-the-fly reprojection support for rasters to QGIS. Very cool!

One of the few things currently missing in QGIS raster layer is the possibility to have other resampling types than nearest neighbour. The problem is that rasters appear pixelated when zooming further than the source raster resolution. So for applications like web mapping, it is important to interpolate the pixel colors and to have a broader display scale range for layers. In the last few weeks, I’ve added bilinear and cubic raster resampling to QGIS (thanks to Canton Solothurn for funding these activities!).

A lot of refactoring was necessary in the raster layer code to add resampling in a clean way. Therefore these changes are available in branch ‘raster_resampler’ of the QGIS github clone (git://github.com/mhugent/Quantum-GIS.git). It probably needs a longer period of testing to make sure every feature of the raster layer class still works properly.

The resampling option can be chosen in the raster properties dialog:

And here is the effect for a three band color image.

Nearest neighbour:

Bilinear:

Cubic:

And here for a palletted background map

Nearest neighbour:

Bilinear:

14:33
Congress Asks NOAA to Consider Charging for DataGEODATA POLICY
sur Planet Geospatial - http://planetgs.com

David Malakoff, Science Magazine, December 2011 (Vol. 334, no. 6051, p. 1337) For decades, scientists at the National Oceanic and Atmospheric Administration (NOAA) have been carving satellite data into customized chunks that help other federal agencies solve some unusual problems—at no cost to the users. But faced with soaring NOAA satellite costs and a bleak [...]

14:04
Congress: NOAA Should Explore Charging for its Satellite Data
sur All Points Blog

For decades, scientists at the National Oceanic and Atmospheric Administration (NOAA) have been carving satellite data into customized chunks that help other federal agencies solve some unusual problems—at no cost to the users. But faced with soaring NOAA satellite costs and a bleak... Continue reading

14:04
Congress: NOAA Should Explore Charging for its Satellite DataAll Points Blog
sur Planet Geospatial - http://planetgs.com

For decades, scientists at the National Oceanic and Atmospheric Administration (NOAA) have been carving satellite data into customized chunks that help other federal agencies solve some unusual problems—at no cost to the users. But faced with soaring NOAA satellite costs and a bleak... Continue reading

13:06
Create a Timelapse Street View Movie
sur Google Maps Mania
The brilliant Address is Approximate mixes stop-motion animation with some timelapse images from Google Maps Street View.

If you want to create your own timelapse movie from Street View then you can follow Digital Inspirations online tutorial How to Create a Time-Lapse Movie with Google Street View. The tutorial explains how to create an AutoHotkey text file that will help you capture a series of Street View images automatically. You can then import the images into Windows Live Movie Maker (or any other video editing software) to create your timelapse movie.

Some Other Street View Timelapse Movies

12:25
New study comparing OpenStreetMap with TomTom from 2009-2011
sur All Points Blog

Alexander Zipf, Chair of GIScience, Department of Geography, University of Heidelberg, Germany shared news of an article comparing OSM and TomTom data in Germany. A new study by the GIScience Research Group of the University of Heidelberg [giscience.uni-hd.de)] that compares... Continue reading

12:25
New study comparing OpenStreetMap with TomTom from 2009-2011All Points Blog
sur Planet Geospatial - http://planetgs.com

Alexander Zipf, Chair of GIScience, Department of Geography, University of Heidelberg, Germany shared news of an article comparing OSM and TomTom data in Germany. A new study by the GIScience Research Group of the University of Heidelberg [giscience.uni-hd.de)] that compares... Continue reading

10:57
Le Stade rennais est-il un club régional ?
sur Blog Géoclip O3, générateur d'observatoires

L'application France découverte, librement accessible, vous permet de consulter nombre de données en mode Open Data, mais aussi de produire des cartes avec vos propres indicateurs. Vous pouvez ensuite intégrer ces cartes dans votre site web.

C'est ainsi que le Stade Rennais Online vient de publier une belle étude illustrée par quelques cartes produites avec France découverte.

4:34
England Adopts Laser Scanners for Crash AssessmentSpatial Sustain
sur Planet Geospatial - http://planetgs.com

The UK department of roads has invested £2.7m for 27 police forces across England to get 3D laser scanning technology for motorway crash assessments. The time of crash closures is said to be reduced by 39 minutes, because of the precise 3D capture of the scene. The ‘economic disruption’ angle to this decision is a [...]
3:25
Create a Ruby on Rails TODO application pt. 2My Corner of the Web
sur Planet Geospatial - http://planetgs.com
Ok, well with Christmas behind us it is time to get on with our project…

I use Pivotal Tracker for creating stories. Creating stories is a new thing for me but it really helps to plan out your app. In fact, if you write your stories well, it make writing our tests easier.

As with any programmer worth their weight in code, I will be creating this app using TDD or BDD depending on how you view those two terms. In my opinion, Test Driven Development consists of writing the tests before writing the code whereas Behavior Driven Development is writing tests to describe the desired behavior that you want. With BDD, it is more that you test what an object does and not so much what it is.

On to Pivotal Tracker.. In pt.1 I listed four stories that I added to my Pivotal Tracker account. (https://www.pivotaltracker.com/projects/441447). One thing that I will not get into is the point estimation for stories in Pivotal Tracker. That is what Google is for.

Lets start with the first story; As a visitor ISBAT create a note. Before we do anything, lets think what it is that we want to do. We want our visitor to be able to create a note. Now I know that a true TODO app would require user registration or just be for myself only but for this we are going to leave it open for all to use. So, lets think through the process..
- Visit the main page
- Click on link ‘Create Note’
- Fill in title with ‘Clean the Garage’
- Fill in description with ‘Get rid of junk and clean out the clutter’
- Select ‘Due by:’ as 2/1/2012
- Click on ‘Save’
Pretty simple, isn’t it? We that is what I will fill in for my Pivotal story under tasks. Now we are looking and thinking about what we want the user experience to be. We have not really concerned ourselves with the workflow and have not written a line of code.

The next thing we need to think of is “what do I expect to happen?” if I follow the above steps.
- I should see ‘Note created successfully’
- I should not see any error messages
- The number of notes should increase by 1
Now we know what we expect to do to create a new note and we know what we expect to happen afterwards. For testing I mentioned that I use Rspec and Capybara. I am not saying that other testing tools are not good; I just have never used anything but. Capybara just continues to amaze me. There are so many different ways to use it that it seems like there is always a solution. It works great with clicking links, making queries, testing Ajax , and more. There once was a time that I tried to learn Selenium for automating tests in Firefox but I found it too cumbersome. Capybara uses Selenium without having to write it!!

I will write my test and post the code in pt.3.
2:19
UK Government Awards Police 2.7 Million Pounds for Laser Scanner PurchasesLiDAR News
sur Planet Geospatial - http://planetgs.com

The UK's Department of Transport announced today that they were awarding police forces a total of 2.7 million pounds for the purchase of laser scanners. Continue reading →

Click Title to Continue Reading...
0:35
ASCE report on the impact of under-investment in water infrastructure in the USBetween the Poles
sur Planet Geospatial - http://planetgs.com
The American Society of Civil Engineers (ASCE) has released a second report in the series called Failure to Act. The first in the series dealt with transportation.

Drinking water

The ASCE points out that water services in the U.S. are decentralized. There are about 170,000 public drinking-water systems, more than half of which serve fewer than 500 people. 54,000 of the water systens are community owned and provide water to more than 264 million people. The other 114,000 are non-community water systems, such as those for campgrounds and schools.

Most of the drinking-water infrastructure, but especially in older cities, is aging. When water systems fail, people are without water, emergency response is impeded, and there can be damage to other types of essential infrastructure. In the worst case water shortages may result in unsanitary conditions and public health issues.

Wastewater

According to the ASCE in 2008 there were about 14,780 wastewater treatment facilities and 19,739 sewer systems About 98 percent of publicly owned treatment systems were municipally owned. Aging pipes and inadequate capacity (SSOs and CSOs) result in the discharge of an estimated 900 billion gallons of untreated sewage into surface waters each year.

Capital investment

Acording to the EPA the capital investment required to maintain and upgrade U.S. drinking water and wastewater treatment systems in 2010 was $91 billion, but only $36 billion of this was funded, resulting in a capital funding gap of $55 billion. According to the ASCE, if this trends persist, by 2020 the funding gap will be $84 billion. By 2040 the funding gap will be $144 billion. With current trends addressing the gap will become increasingly more expensive, and waters will be polluted.

The ASCE report estimates the impact of not addressing the funding gap will have on househilds and businesses and on the national economy. The major impacts will be
- Water shortages will result in higher rates and major outlays by businesses and households, including expenditures to move to where infrastructure is still reliable; purchasing and installing equipment to conserve water or recycle water; and increasing reliance on self-supplied water and wastewater treatment.
- Increased medical costs as a reult of increases in water-borne illnesses.
The estimated expenses to businesses of unreliable water delivery and wastewater treatment is estimated to be $147 billion by 2020, and $59 billion for households. The total impact of increased costs and reduced income will decrease the standard of living for families by almost $900 per year by 2020.

By 2020, the predicted deficit for sustaining water delivery and wastewater treatment infrastructure will be $84 billion. In a worst case scenario, the U.S. will lose nearly 700,000 jobs by 2020 and 1.4 million jobs by 2040. Between now and 2020, the cumulative loss in business sales will be $734 billion and the cumulative loss to the U.S. GDP will be $416 billion. By 2040, the impact will be $481 billion in lost business sales and $252 billion in lost GDP.

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